Infrared face recognition: a comprehensive review of methodologies and databases

Automatic face recognition is an area with immense practical potential which includes a wide range of commercial and law enforcement applications. Hence it is unsurprising that it continues to be one of the most active research areas of computer vision. Even after over three decades of intense research, the state-of-the-art in face recognition continues to improve, benefitting from advances in a range of different research fields such as image processing, pattern recognition, computer graphics, and physiology. Systems based on visible spectrum images, the most researched face recognition modality, have reached a significant level of maturity with some practical success. However, they continue to face challenges in the presence of illumination, pose and expression changes, as well as facial disguises, all of which can significantly decrease recognition accuracy. Amongst various approaches which have been proposed in an attempt to overcome these limitations, the use of infrared (IR) imaging has emerged as a particularly promising research direction. This paper presents a comprehensive and timely review of the literature on this subject. Our key contributions are: (i) a summary of the inherent properties of infrared imaging which makes this modality promising in the context of face recognition, (ii) a systematic review of the most influential approaches, with a focus on emerging common trends as well as key differences between alternative methodologies, (iii) a description of the main databases of infrared facial images available to the researcher, and lastly (iv) a discussion of the most promising avenues for future research.Comment: Pattern Recognition, 2014. arXiv admin note: substantial text overlap with arXiv:1306.160

Long-lived anomalous thermal diffusion induced by elastic cell membranes on nearby particles

The physical approach of a small particle (virus, medical drug) to the cell membrane represents the crucial first step before active internalization and is governed by thermal diffusion. Using a fully analytical theory we show that the stretching and bending of the elastic membrane by the approaching particle induces a memory in the system which leads to anomalous diffusion, even though the particle is immersed in a purely Newtonian liquid. For typical cell membranes the transient subdiffusive regime extends beyond 10 ms and can enhance residence times and possibly binding rates up to 50\%. Our analytical predictions are validated by numerical simulations.Comment: 13 pages and 5 figures. The Supporting Information is included. Manuscript accepted for publication in Phys. Rev.

Human Face Recognition

Face recognition, as the main biometric used by human beings, has become more popular for the last twenty years. Automatic recognition of human faces has many commercial and security applications in identity validation and recognition and has become one of the hottest topics in the area of image processing and pattern recognition since 1990. Availability of feasible technologies as well as the increasing request for reliable security systems in today’s world has been a motivation for many researchers to develop new methods for face recognition. In automatic face recognition we desire to either identify or verify one or more persons in still or video images of a scene by means of a stored database of faces. One of the important features of face recognition is its non-intrusive and non-contact property that distinguishes it from other biometrics like iris or finger print recognition that require subjects’ participation. During the last two decades several face recognition algorithms and systems have been proposed and some major advances have been achieved. As a result, the performance of face recognition systems under controlled conditions has now reached a satisfactory level. These systems, however, face some challenges in environments with variations in illumination, pose, expression, etc. The objective of this research is designing a reliable automated face recognition system which is robust under varying conditions of noise level, illumination and occlusion. A new method for illumination invariant feature extraction based on the illumination-reflectance model is proposed which is computationally efficient and does not require any prior information about the face model or illumination. A weighted voting scheme is also proposed to enhance the performance under illumination variations and also cancel occlusions. The proposed method uses mutual information and entropy of the images to generate different weights for a group of ensemble classifiers based on the input image quality. The method yields outstanding results by reducing the effect of both illumination and occlusion variations in the input face images

Distortion Robust Biometric Recognition

abstract: Information forensics and security have come a long way in just a few years thanks to the recent advances in biometric recognition. The main challenge remains a proper design of a biometric modality that can be resilient to unconstrained conditions, such as quality distortions. This work presents a solution to face and ear recognition under unconstrained visual variations, with a main focus on recognition in the presence of blur, occlusion and additive noise distortions. First, the dissertation addresses the problem of scene variations in the presence of blur, occlusion and additive noise distortions resulting from capture, processing and transmission. Despite their excellent performance, ’deep’ methods are susceptible to visual distortions, which significantly reduce their performance. Sparse representations, on the other hand, have shown huge potential capabilities in handling problems, such as occlusion and corruption. In this work, an augmented SRC (ASRC) framework is presented to improve the performance of the Spare Representation Classifier (SRC) in the presence of blur, additive noise and block occlusion, while preserving its robustness to scene dependent variations. Different feature types are considered in the performance evaluation including image raw pixels, HoG and deep learning VGG-Face. The proposed ASRC framework is shown to outperform the conventional SRC in terms of recognition accuracy, in addition to other existing sparse-based methods and blur invariant methods at medium to high levels of distortion, when particularly used with discriminative features. In order to assess the quality of features in improving both the sparsity of the representation and the classification accuracy, a feature sparse coding and classification index (FSCCI) is proposed and used for feature ranking and selection within both the SRC and ASRC frameworks. The second part of the dissertation presents a method for unconstrained ear recognition using deep learning features. The unconstrained ear recognition is performed using transfer learning with deep neural networks (DNNs) as a feature extractor followed by a shallow classifier. Data augmentation is used to improve the recognition performance by augmenting the training dataset with image transformations. The recognition performance of the feature extraction models is compared with an ensemble of fine-tuned networks. The results show that, in the case where long training time is not desirable or a large amount of data is not available, the features from pre-trained DNNs can be used with a shallow classifier to give a comparable recognition accuracy to the fine-tuned networks.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

A novel strategy for molecular interfaces optimization: the case of ferritin-transferrin receptor interaction

Protein-protein interactions regulate almost all cellular functions and rely on a fine tune of surface amino acids properties involved on both molecular partners. The disruption of a molecular association can be caused even by a single residue mutation, often leading to a pathological modification of a biochemical pathway. Therefore the evaluation of the effects of amino acid substitutions on binding, and the ad hoc design of protein-protein interfaces, is one of the biggest challenges in computational biology. Here, we present a novel strategy for computational mutation and optimization of protein-protein interfaces. Modeling the interaction surface properties using the Zernike polynomials, we describe the shape and electrostatics of binding sites with an ordered set of descriptors, making possible the evaluation of complementarity between interacting surfaces. With a Monte Carlo approach, we obtain protein mutants with controlled molecular complementarities. Applying this strategy to the relevant case of the interaction between Ferritin and Transferrin Receptor, we obtain a set of Ferritin mutants with increased or decreased complementarity. The extensive molecular dynamics validation of the method results confirms its efficacy, showing that this strategy represents a very promising approach in designing correct molecular interfaces

Face recognition using infrared vision

Au cours de la dernière décennie, la reconnaissance de visage basée sur l’imagerie infrarouge (IR) et en particulier la thermographie IR est devenue une alternative prometteuse aux approches conventionnelles utilisant l’imagerie dans le spectre visible. En effet l’imagerie (visible et infrarouge) trouvent encore des contraintes à leur application efficace dans le monde réel. Bien qu’insensibles à toute variation d’illumination dans le spectre visible, les images IR sont caractérisées par des défis spécifiques qui leur sont propres, notamment la sensibilité aux facteurs qui affectent le rayonnement thermique du visage tels que l’état émotionnel, la température ambiante, la consommation d’alcool, etc. En outre, il est plus laborieux de corriger l’expression du visage et les changements de poses dans les images IR puisque leur contenu est moins riche aux hautes fréquences spatiales ce qui représente en fait une indication importante pour le calage de tout modèle déformable. Dans cette thèse, nous décrivons une nouvelle méthode qui répond à ces défis majeurs. Concrètement, pour remédier aux changements dans les poses et expressions du visage, nous générons une image synthétique frontale du visage qui est canonique et neutre vis-à-vis de toute expression faciale à partir d’une image du visage de pose et expression faciale arbitraires. Ceci est réalisé par l’application d’une déformation affine par morceaux précédée par un calage via un modèle d’apparence active (AAM). Ainsi, une de nos publications est la première publication qui explore l’utilisation d’un AAM sur les images IR thermiques ; nous y proposons une étape de prétraitement qui rehausse la netteté des images thermiques, ce qui rend la convergence de l’AAM rapide et plus précise. Pour surmonter le problème des images IR thermiques par rapport au motif exact du rayonnement thermique du visage, nous le décrivons celui-ci par une représentation s’appuyant sur des caractéristiques anatomiques fiables. Contrairement aux approches existantes, notre représentation n’est pas binaire ; elle met plutôt l’accent sur la fiabilité des caractéristiques extraites. Cela rend la représentation proposée beaucoup plus robuste à la fois à la pose et aux changements possibles de température. L’efficacité de l’approche proposée est démontrée sur la plus grande base de données publique des vidéos IR thermiques des visages. Sur cette base d’images, notre méthode atteint des performances de reconnaissance assez bonnes et surpasse de manière significative les méthodes décrites précédemment dans la littérature. L’approche proposée a également montré de très bonnes performances sur des sous-ensembles de cette base de données que nous avons montée nous-mêmes au sein de notre laboratoire. A notre connaissance, il s’agit de l’une des bases de données les plus importantes disponibles à l’heure actuelle tout en présentant certains défis.Over the course of the last decade, infrared (IR) and particularly thermal IR imaging based face recognition has emerged as a promising complement to conventional, visible spectrum based approaches which continue to struggle when applied in the real world. While inherently insensitive to visible spectrum illumination changes, IR images introduce specific challenges of their own, most notably sensitivity to factors which affect facial heat emission patterns, e.g., emotional state, ambient temperature, etc. In addition, facial expression and pose changes are more difficult to correct in IR images because they are less rich in high frequency details which is an important cue for fitting any deformable model. In this thesis we describe a novel method which addresses these major challenges. Specifically, to normalize for pose and facial expression changes we generate a synthetic frontal image of a face in a canonical, neutral facial expression from an image of the face in an arbitrary pose and facial expression. This is achieved by piecewise affine warping which follows active appearance model (AAM) fitting. This is the first work which explores the use of an AAM on thermal IR images; we propose a pre-processing step which enhances details in thermal images, making AAM convergence faster and more accurate. To overcome the problem of thermal IR image sensitivity to the exact pattern of facial temperature emissions we describe a representation based on reliable anatomical features. In contrast to previous approaches, our representation is not binary; rather, our method accounts for the reliability of the extracted features. This makes the proposed representation much more robust both to pose and scale changes. The effectiveness of the proposed approach is demonstrated on the largest public database of thermal IR images of faces on which it achieves satisfying recognition performance and significantly outperforms previously described methods. The proposed approach has also demonstrated satisfying performance on subsets of the largest video database of the world gathered in our laboratory which will be publicly available free of charge in future. The reader should note that due to the very nature of the feature extraction method in our system (i.e., anatomical based nature of it), we anticipate high robustness of our system to some challenging factors such as the temperature changes. However, we were not able to investigate this in depth due to the limits which exist in gathering realistic databases. Gathering the largest video database considering some challenging factors is one of the other contributions of this research

A Proper Orthogonal Decomposition-based inverse material parameter optimization method with applications to cardiac mechanics

We are currently witnessing the advent of a revolutionary new tool for biomedical research. Complex mathematical models of "living cells" are being arranged into representative tissue assemblies and utilized to produce models of integrated tissue and organ function. This enables more sophisticated simulation tools that allows for greater insight into disease and guide the development of modern therapies. The development of realistic computer models of mechanical behaviour for soft biological tissues, such as cardiac tissue, is dependent on the formulation of appropriate constitutive laws and accurate identification of their material parameters. The main focus of this contribution is to investigate a Proper Orthogonal Decomposition with Interpolation (PODI) based method for inverse material parameter optimization in the field of cardiac mechanics. Material parameters are calibrated for a left ventricular and bi-ventricular human heart model during the diastolic filling phase. The calibration method combines a MATLAB-based Levenberg Marquardt algorithm with the in-house PODIbased software ORION. The calibration results are then compared against the full-order solution which is obtained using an in-house code based on the element-free Galerkin method, which is assumed to be the exact solution. The results obtained from this novel calibration method demonstrate that PODI provides the means to drastically reduce computation time but at the same time maintain a similar level of accuracy as provided by the conventional approach

Hydrodynamic mobility of a solid particle nearby a spherical elastic membrane. II. Asymmetric motion

In this paper, we derive analytical expressions for the leading-order hydrodynamic mobility of a small solid particle undergoing motion tangential to a nearby large spherical capsule whose membrane possesses resistance towards shearing and bending. Together with the results obtained in the first part (Daddi-Moussa-Ider and Gekle, Phys. Rev. E {\bfseries 95}, 013108 (2017)) where the axisymmetric motion perpendicular to the capsule membrane is considered, the solution of the general mobility problem is thus determined. We find that shearing resistance induces a low-frequency peak in the particle self-mobility, resulting from the membrane normal displacement in the same way, although less pronounced, to what has been observed for the axisymmetric motion. In the zero frequency limit, the self-mobility correction near a hard sphere is recovered only if the membrane has a non-vanishing resistance towards shearing. We further compute the particle in-plane mean-square displacement of a nearby diffusing particle, finding that the membrane induces a long-lasting subdiffusive regime. Considering capsule motion, we find that the correction to the pair-mobility function is solely determined by membrane shearing properties. Our analytical calculations are compared and validated with fully resolved boundary integral simulations where a very good agreement is obtained.Comment: 17 pages, 9 figures and 64 references. Manuscript accepted for publication in Phys. Rev.

Free vibration of symmetric angly-plane layered truncated conical shells under classical theory

Truncated conical shell finds wide ranging of engineering applications. They are used in space crafts, robots, shelters, domes, tanks, nozzles and in machinery devices. Thus, the study of their vibrational characteristics has long been of interest for the designers. The use of the lamination for the structures leads to design with the maximum reliability and minimum weight. Moreover, the study of free vibration of laminated conical shells has been treated by a number of researchers. Irie et al. (1982) studied free vibration of conical shells with variable thickness using Rayleigh-Ritz method of solution. Wu and Wu (2000) provided 3D elasticity solutions for the free vibration analysis of laminated conical shells by an asymptotic approach. Wu and Lee (2001) studied the natural frequencies of laminated conical shells with variable stiffness using the differential quadrature method under first-order shear deformation theory (FSDT). Tripathi et al. (2007) studied the free vibration of composite conical shells with random material properties of the finite element method. Civalek (2007) used the Discrete Singular Convolution (DSC) to investigate the frequency response of orthotropic conical and cylindrical shells. Sofiyez et al. (2009) studied the vibrations of orthotropic non-homogeneous conical shells with free boundary conditions. Ghasemi et al. (2012) presented their study of free vibration of composite conical shells which was investigated under various boundary conditions using the solution of beam function and Galerkin method. Viswanathan et al. (2007, 2011) studied free vibration of laminated cross-ply plates, including shear deformation, symmetric angle-ply laminated cylindrical shells of variable thickness with shear deformation theory using the spline collocation method. In the present work, free vibration of symmetric angle-ply laminated truncated conical shells is analyzed and displacement functions are approximated using cubic and quantic spline and collocation procedure is applied to obtain a set of field equations. The field equations along with the equations of boundary conditions yield a system of homogeneous simultaneous algebraic equations on the assumed spline coefficients which resulting to the generalized eigenvalue problem. This eigenvalue problem is solved using eigensolution technique to get as many eigenfrequencies as required. The effect of circumferential mode number, length ratio, cone angle, ply angles and number of layers under two boundary conditions on the frequency parameter is studied for three- and five- layered conical shells consisting of two types of layered materials